We describe in this paper a new hybrid approach for optimization combining Particle Swarm Optimization (PSO) and Genetic Algorithms (GAs) using Fuzzy Logic to integrate the results. The new evolutionary method combines the advantages of PSO and GA to give us an improved FPSO+FGA hybrid method. Fuzzy Logic is used to combine the results of the PSO and GA in the best way possible. The new hybrid ...

The modern methods for power system load and energy prediction are usually based on artificial neural networks and fuzzy logic, which present satisfactory results. However, the estimation of the confidence intervals can not be applied directly, unlike to the classical forecasting methods. The objective of this paper is to present an optimized fuzzy logic method for midterm energy forecasting, w...

The dynamic behavior of an industrial tunneltype furnace is of the fundamental importance for the quality of the processed products. The knowledge of the furnace dynamics can make the control of the system easier as well as it can eliminate certain operational problems. The various subsystems existent in a tunnel-type furnace are usually controlled by conventional techniques and independent con...

In this paper, different semi-active control strategies for non-linear quarter car model equipped with controllable magneto-rheological (MR) shock absorbers and fuzzy logic controller are compared. Polynomial model is selected to characterize the experimental results of MR shock absorber. A combination of Forward Fuzzy Logic Controller (FFLC) and Inverse Fuzzy Logic Controller (IFLC) is designe...

This article explores a novel fuzzy logic controller (FLC) based threephase shunt active power line conditioners (APLC) for power quality improvements due to the non-linear loads. The fuzzy logic controller is Mamdani-type and linguistic description, so it does not necessitate a mathematical model of the system. The FLC controller is capable of controlling harmonic current and dc-side capacitor...

Conventionally modelling and simulation of complex nonlinear systems has been to construct a mathematical model and examine the system’s evolution or its control. This kind of approach can fail for many of the very large non-linear and complex systems being currently studied. With the invention of new advanced high-speed computers and the application of artificial intelligence paradigms new tec...

This paper investigates a hybrid methodology that combines fuzzy logic and neural networks, Fuzzy Cognitive Map (FCM), for modeling and controlling Supervisory Control Systems. A mathematical description of Fuzzy Cognitive Maps (FCM) will be presented and new construction methods will be extensively examined. A Fuzzy Cognitive Map will be developed to model and control a process example and the...

This paper investigates a hybrid methodology that combines fuzzy logic and neural networks, Fuzzy Cognitive Map (FCM), for modeling and controlling Supervisory Control Systems. A mathematical description of Fuzzy Cognitive Maps (FCM) will be presented and new construction methods will be extensively examined. A Fuzzy Cognitive Map will be developed to model and control a process example and the...

In this paper we want to describe proposal of the fuzzy control of synchronous motor with permanent magnet and impact of deployment of membership functions of fuzzy controller on a regulation quality of a synchronous permanent magnet motor (PMSM). In the first part of this paper is described mathematical model of synchronous motor with permanent magnets and designed controller by using fuzzy lo...

This project presents a method of improving the speed profile, torque and flux using stator estimation method. This discusses the problems associated with the error in stator Resistance and proposes an analytical approach to investigate its effect on the actual and estimated variables of a induction motor. Based on how this error affects the estimated angle between the stator flux and current v...